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Over the past year, the world has had the opportunity to experiment with new LLM-powered generative AI platforms and discover how they might overcome longstanding business challenges. At Sixfold, saw the potential—and necessity—of applying gen AI in insurance underwriting.

Today, too many underwriters are overwhelmed with high-volume (but not necessarily high-value) tasks. They’re charged with collecting and synthesizing complex data from disparate sources, while subsequently acting as the key coordination points with agents and brokers.

Underwriters have exponentially more responsibilities but have been given only incrementally improved tools (at best). As a result, companies are hitting the inevitable limits of manual processes.

An automated underwriting system to free the underwriters

According to some recent data, underwriters spend almost half of their work lives on administrative activities. This reduced capacity leads to lost business and inevitably places downward pressure on Gross Written Premiums (GWPs).

We started Sixfold because we saw the opportunity for gen AI to free underwriters from that growing administrative weight. Think about it: what would you accomplish if you suddenly had 40% of your work-life back? Even better: what if the tasks you no longer had to do were the ones you liked least? All that excess administrative work is… work.

The role of underwriter has long since moved past just risk selection and pricing. As McKinsey frames it: modern underwriting requires “a comprehensive set of capabilities across hard and soft skills, qualitative judgments about future industry performance.” Machines handle numberwork and repetitive tasks better anyway, so let them have it and free humans to generate value using their subjective, uniquely human skill sets.

Underwriting should be a creative, multifaceted, and dare I say, even… joyful endeavor. I believe play a key role in this regard by empowering underwriters to focus on what they love most: making deals and closing business.

Generative AI, your new underwriting assistant

With gen AI, every underwriter can have their own virtual team of researchers and administrative assistants who know exactly what information the “boss” needs.

Guided by decades of collective industry experience, our platform collects and synthesizes data from third-party and proprietary sources, spots patterns, and summarizes risk in the insurer’s UW format—all using clear natural language.

The platform ingests and models each company's unique risk appetite, so it can surface relevant information and accelerate UW decisioning. Sixfold highlights application inconsistencies for additional underwriter review—for example, if a case falls within a potentially higher risk category, the platform pinpoints the precise data points that require closer evaluation.

With Sixfold, companies are accelerating submission-to-quote cycles by as much as 43%, clearing backlogged queues, and massively increasing GWP per underwriter. As for the underwriters themselves, they’re embracing the platform once they see the opportunity to move faster, be more productive, and make more money.

AI can’t replace underwriters, but it can amplify their potential

Across industries, there’s anxiety around potential disruptions gen AI will have on the labor market. I don’t see it that way. I view this technology as continuing the long technological tradition of freeing humans from mundane work.

Word processing software, for example, didn’t replace editors and writers—it allowed them to work faster while leaving the icky carbon paper, whiteout, and typewriter ink behind. All the while, the number of writers, editors, and communication workers continues to grow. Similarly, accounting software didn’t remove accountants, it just removed the need for accountants to be calculators and as a result, they could be more creative and specialized. Indeed, there’s currently a nationwide shortage of accountants. Moreover, as the latest data shows, they’re earning more than ever.

I see gen AI having a similar impact on insurance by emphasizing the creative and specialized side of the underwriting role, which can make them more satisfied, productive, and successful. Better yet, more successful underwriters have knock-on benefits down the value chain to agents and brokers (who get yes/no answers quicker) and the organization as a whole (through greatly improved GWP).

I believe there’s never been a better, or more joyful time to be an underwriter.

In today's evolving insurance landscape, the integration of generative AI in underwriting is one huge key to staying ahead. Here are a few considerations as you assess solutions:

🎯 1. Determine Your Priorities

‍Underwriting is complex, and each step of the process requires different types of generative solutions. Gen AI can greatly improve the intake, classification, summarization, and policy binding suggestions for risks. In the early days, we’ve seen most underwriters prioritize two key use-cases:

1) Fix the “front door” problem by enhancing the triaging and routing of submissions and

2) Summarize and classify submissions according to the insurer’s custom risk appetite.

🔮 2. This Isn’t Your Grandparents’ AI

The rules of generative AI are different from the previous generations of AI. Prior efforts at AI in underwriting have required mountains of training data to even get started. That’s not the case with Gen AI underwriting and you can start seeing impacts very quickly. As important, gen AI underwriting isn’t the dreaded “black box” that insurers and regulators fear. Instead, Gen AI underwriting models can “show their work” and explain all the steps they take to assist an underwriter.

🧠 3. Understand the Models

Navigating generative AI for underwriting requires a comprehensive understanding of the different LLMs and vector databases in the market. LLMs are not all equal. Each LLM has its own strengths and weaknesses. Some are better at summarization, some at reasoning, and others are better at helping an insurer to find its voice. And some still require special care to control hallucinations. Understanding the differences between models helps you select the most suitable LLM (or LLMs) for your specific underwriting needs. For example, we deploy 5 different fit-for-purpose LLMs for a variety of gen AI underwriting.

⚖️ 4. Start With Compliance at the Table

Compliance is paramount in the evolving world of generative AI. It is crucial to ensure your compliance and legal teams have a seat at the table. When set up optimally, generative AI can help streamline compliance procedures and address legal concerns. Emphasizing the shift from bias to traceability is vital as regulators increasingly stress the importance of transparent and accountable AI systems, ensuring that organizations remain ethically and legally sound in their AI-driven endeavors.

💡 5. Built-for-Purpose Tech > ChatGPT

While publicly available gen AI models like ChatGPT and Bard have their place in the consumer world, they can’t be used at an insurance carrier. The regulated nature of insurance coupled with data privacy concerns means you must use purpose-built technology for underwriting. With each insurance carrier possessing a distinct risk appetite and set of guidelines, built-for-purpose generative AI incorporates (and keeps secret!) your underwriting protocols.
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Sixfold is the first generative AI created exclusively for insurance underwriters. Our purpose-built AI increases an insurance carrier’s capacity, accuracy, and compliance. The Sixfold AI intelligently ingests, routes, classifies, and summarizes submissions, providing underwriters with trustworthy, data-driven policy recommendations in a user-friendly format. Sixfold provides full AI traceability, ensuring your underwriting processes adhere to your underwriting manual and regulations, enhancing trust and reliability in every decision.

This article was originally posted on LinkedIn

Working in enterprise tech - an industry that has notoriously struggled to stay on the cutting edge - I never needed much convincing that AI would one day unlock massive opportunity. While we are nowhere close to meaningful adoption of AI, that’s where we’re headed.

The first wave of generative AI has been horizontal with the release of GPT-4, Anthropic, Bard, and others. But the next wave will be vertical, marrying the summarization and reasoning superpowers of the LLMs with specially-trained models and industry expertise.

This is why today, I’m excited to announce the launch of Sixfold, the first generative artificial intelligence trained to solve the hardest problems in the insurance industry.

With $6.5 million in seed backing from Bessemer Venture Partners and Crystal Venture Partners, and leadership with decades of insurance experience, Sixfold is poised to rapidly transform how the insurance industry thinks about and uses AI.

To start, Sixfold Gen AI will focus on one of the most intractable challenges in insurance: the inefficiency of underwriting.

Underwriting is an art form, requiring human-level pattern recognition to capture all of the things that go into understanding a complex risk. For years, insurers have struggled to extract clear rules and standards for assessing risk because there has simply been too much information. Insurance carriers have a “front-door problem”: because of how manual and time-intensive the underwriting process is, insurers can’t provide quotes on all of the opportunities that come their way.

A smart underwriting platform like you’ve never seen before.

Prior attempts at AI in insurance haven’t gained much traction because they took a “black box” approach and thought they knew better than the underwriters. These failed attempts need way too much data and haven’t produced consistent results. Instead, we’ve trained generative AI models to "understand" all of this information and assist humans with the manual assessment. With the Sixfold Assistant, underwriters will be able to quickly evaluate and rate all submissions, thus improving underwriters’ capacity as well as the accuracy and traceability of their decisions.

Today, the Sixfold Assistant is best positioned to eliminate a lot of the “grunt work” that underwriters deal with on a daily basis: tracking down information from third parties, poring through thousands of pages of documents, and making sense of unstructured data. Sixfold will serve as a co-pilot to underwriters, plugging into existing technology so insurers don’t need to overhaul legacy systems in order to take advantage of Sixfold’s capabilities.

We’re thrilled to be launching with our customer BTIS, the commercial insurance provider focused on the construction and building trades industry. Sixfold will be an important tool for BTIS underwriters to improve the speed and accuracy of their underwriting efforts. Sixfold will ultimately make BTIS more competitive by allowing its underwriters to spend less time poring over data and more time issuing policies to its customers.

Sixfold is partnering at launch with BuildZoom, the leading provider of contractor profile data, property building permit data and contractor sourcing services. Sixfold will also expand its partner ecosystem to include consulting and advisory firms, cloud providers, risk and prior loss providers and medical records providers.

Sixfold’s initial focus will be on the commercial property & casualty and life insurance sectors, with plans to expand across the entire insurance industry, going after the over $100 billion spent annually in the US to underwrite insurance.

I’m particularly excited to launch Sixfold because of who I’m doing it with.

Our founding team is made up of former founders and operators, with deep experience in highly-regulated industries, including decades in insurance. Jane Tran is our COO and co-founder. Jane and I spent years working together as founding team members at Unqork, the $2 billion enterprise no-code platform. Our CTO and co-founder Brian Moseley, joins us from American Express where he was Head of Developer Experience.

A huge thanks to Charles Birnbaum and Jeremy Levine at Bassemer Venture Partners, and Jonathan Crystal and Stephen McGovern at Crystal Venture Partners for supporting us in this journey, to our ambitious customers, and to our partners.

Let’s rewrite the rules of insurance together!

This announcement was originally posted on LinkedIn

No one became an underwriter because they love writing case notes. But that’s where a huge amount of time goes today. Referral notes, peer review memos, audit documentation, written and rewritten, case after case.

At multiple steps in the process, underwriters need to carefully document the risk story manually.

• A single case can take an hour, often several hours, to document.
• Underwriters are doing this work while balancing dozens of other tasks: reviewing new submissions, responding to brokers, preparing quotes, and managing existing accounts.
• Multiply that across a typical team handling hundreds of submissions each week. The result is thousands of hours spent each year on documentation alone.

And the real costs for insurers go beyond time.

1. Quotes go out slower to brokers and clients in markets where speed wins deals.
2. Audit and compliance risks increase when documentation is inconsistent.
3. When experienced underwriters leave, so does the knowledge of how to capture the right details in the risk stories.

Documentation is needed to make smart underwriting decisions and meet compliance standards. The question is: how do we get it without slowing teams down?

80% Automation, 20% Judgment.

Sixfold’s Narratives feature automates the repetitive parts of this process and standardizes how risk is communicated across the organization. It automatically generates risk narratives that match each insurer’s tone and format, while giving underwriters the flexibility to apply their own judgment where it matters.

[Shirley video explaining the feature]

Sixfold’s Narratives are built to:

• Align with the insurer’s unique risk appetite
• Surface key facts and risk insights that matter most
• Adhere to required documentation standards and formats

On average, underwriters save more than 90 minutes per case with this capability. For a 10-person team handling 200 cases per week, that adds up to over 20,000 hours saved every year, time they can spend underwriting, not writing.

“Think of all the documents you have to create for administrative purposes, maybe it’s a referral summary, maybe an account summary attached to a submission after a decision. Anything that requires you to synthesize the risk overall.

Sixfold is doing 80% of that for you: bringing together all the facts. Then the underwriter just adds the last 20%, the judgment call.”

-   Laurence, Head of Customers and Partnerships

Proven with Zurich’s North America Team

Narratives were developed and validated through the Global Zurich Insurance Innovation Championship.

Over a 6-week sprint with Zurich’s North America Middle Market team, Sixfold:

• Partnered with 16 underwriters and was used in 80%+ of their live submissions
• Processed nearly 4,000 pages of submission and web data
• Achieved 90 minutes time savings per submission on average

Sixfold was mentioned as a key driver in Zurich’s effort on capitalizing on new technology to improve accuracy and efficiency in underwriting process at Zurich’s Investor Day 2024

Add in a quote from Amy or Zurich Underwriter and link to blog post/ other content from Zurich - interview  to be added later :)

One Tool = Multiple Use Cases

The summarization and customization capability of this feature supports a variety of steps in the underwriting workflow, from intake through to decision documentation.

AI That Actually Gets Used

The Narratives feature is a great starting point for insurers looking to bring AI into underwriting workflows today.

It takes the repetitive parts of the job off underwriters’ hands without requiring them to change how they already work. It simply gives them back more time to focus on the parts of underwriting they enjoy.

“I already have a picture of this risk in 20 seconds instead of formulating it on my own.”[3] [4] [5]
Zurich Underwriter

When underwriters experience that impact immediately, with fewer hours spent writing up cases and fewer rounds of revisions, adoption happens easily. AI becomes part of the flow of work because it genuinely makes the day-to-day tasks so much easier.

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